Work engagement is defined as the intentional allocation of personal resources to actively take responsibility for professional tasks (Korunka et al., 2009). In teaching, it is characterized by vigour, which includes energy and mental resilience, and commitment, which includes enthusiasm and inspiration (Hakanen, Bakker, & Schaufeli, 2006). Teachers with higher work engagement are more energetic and committed to their profession (Greenier, Derakhshan, & Fathi, 2021). Internal factors such as compassion, career satisfaction, agency, efficacy, and well-being significantly influence work engagement. These factors are explained by the job-demands-resources (JD-R) model (Demerouti et al., 2001) and self-determination theory (SDT; Ryan and Deci, 2000, 2001). The JD-R model (Demerouti et al., 2001; Bakker and Demerouti, 2007) posits a balance between demands and resources, whereas SDT (Ryan and Deci, 2000, 2001) suggests a fulfilment of individual's aspirations or psychological needs. Although a considerable amount of research has examined the internal factors of teachers' work engagement through quantitative research, few studies have focused on external factors such as AI tools and professional learning communities from a qualitative perspective.

The concept of a professional learning community (PLC) has received considerable attention since the 1990s, and PLCs have played an increasingly important role in educational reform in various countries (Stoll et. al., 2006). The core idea of PLCs is that they enable groups of educators to collectively challenge and improve their practice through shared vision, collaborative reflection and mutual learning with the aim of promoting student learning (Hord, 1997; Stoll et. al., 2006). Numerous studies suggest that well-implemented PLCs contribute significantly to teacher job satisfaction, teacher well-being, teacher innovation, teacher performance, and teacher retention. There is extensive evidence of a positive relationship between PLCs and desired teacher outcomes, yet little empirical evidence of the relationship between PLCs and teacher work engagement.

ChatGPT, a sophisticated natural language processing system, mimics human dialogue in a variety of languages and styles (Ahmad, Murugesan, & Kshetri, 2023). Since its launch in 2022, it has gained popularity and is considered by many to be one of the most powerful AI tools in human history (OpenAI, 2023; Rudolph et al., 2023). The use of AI tools, particularly ChatGPT, in education can speed up access to resources, help create lessons, present summaries, generate writing topics, and facilitate interactive dialogues. Although there is no conclusive research on the causal relationship between teachers' AI literacy and their professional engagement, a UNESCO report states that AI competence is an essential prerequisite for promoting employability in current and future professions (Miao, F., & Cukurova, M, 2024). In other words, the use of AI tools in teaching has become indispensable, and exploring how to better use these tools is an important issue for teacher engagement.

China is experiencing a significant decline in the number of kindergartens for the first time since 2008. This decline is evidenced by the closure of at least 20,400 kindergartens across the country since 2022. This means that an average of 40 kindergartens are closing every day. Concurrently, a significant number of preschool teachers have been resigning from their positions. In 2023 alone, the number of full-time preschool teachers decreased by 170,000, and some early childhood teachers have been compelled to seek alternative employment opportunities (CCTV news, 2024). In response to these developments, some kindergartens have been exploring innovative approaches to teaching and service delivery. Sunny Kindergarten is one such institution that has adopted new methodologies.

In light of those mentioned above, this study explores how a kindergarten promotes teacher engagement through both a PLC and an AI tool in the context of kindergarten shut-down crisis in China.

The bounded system for this research was one preschool located in one of the public estates in a city in the eastern provinces of China. Its identity and the names of its teachers are anonymized in this paper. The research employed a qualitative case study. Documents concerning the preschool context, including teachers' reflective journals, teaching and research activities, and data on children's daily behavior recorded by teachers through the AI platform, were collected and analyzed in order to establish the social and academic profile of the school. The Kindergarten AI Platform Tool (hereafter referred to as the D-AI Platform) is an artificial intelligence teaching aid system based on ChatGPT. Teachers record children's daily behaviour through voice input, taking pictures and other forms and upload them to the D-AI Platform. The platform relies on ChatGPT to organise, mark, generate tables, text and other functions to assist teachers with teaching evaluation, children profile creation and other work. Faced with the new challenge of the D-AI platform, Sunny Kindergarten established a PLC to enhance the teachers' work engagement. The main focus of the PLC was to help teachers effectively use the AI platform, reduce their workload and improve their work efficiency, thus promoting their professional growth. All teachers in the PLC, including the principal, deputy principal and experts from a university (N=10), were interviewed individually. Semi-structured interviews were prepared after refining interview questions through several iterations to increase clarity and relevance, and to guide the interviewer while following the natural flow of participants' remarks. The researchers attended and documented the PLC activities at Sunny Kindergarten. Each participant was interviewed once, with interviews lasting between 60 and 90 minutes. The interviews focused on the opportunities and challenges that the implementation of the D-AI platform brought to the work of the teachers, the experience of using the AI platform, the benefits gained from participating in the PLC and the support of the principal. Each interview was recorded with the consent of the interviewee and automatically transcribed simultaneously. An initial memo and summary were written immediately after the interview. To ensure trustworthiness, the two researchers triangulated and constructed emergent matrices. Member checks were also carried out by asking participants to read and comment on themes and direct quotes.

This study demonstrates that by proactively promoting the integration of AI tools within a PLC and cultivating shared values, the principal of Sunny Kindergarten has effectively enhanced teachers' work engagement and advanced their critical thinking and reflective skills to a large extent. Firstly, the maintenance of teachers' work engagement is contingent not only on psychological intrinsic support, but also, and more importantly, on substantial external resource support, a factor that is seldom addressed in the extant literature. Initially, the teachers of PLC exhibited commitment, enthusiasm and resilience in their work. However, they demonstrated a lack of AI skills, necessary professional knowledge and effective methodological guidance. This resulted in repetitive work and an absence of professional development. Subsequently, the principal actively introduced AI tools and appointed university researchers as external resources for the PLC's teaching and research activities. This development led to increased teacher engagement in their work, accompanied by a shift in perspective and approach to thinking, analysing and solving problems. This development resulted in the establishment of a quadruple link between teachers, experts, AI and students, thereby disrupting the conventional teaching and research paradigm. Secondly, with regard to AI tools, both the functionalities they offer and the teachers' proficiency in using them are still in their infancy. While AI has demonstrated proficiency in monitoring and managing students (e.g. locating and profiling children), the ability to precisely describe students' behaviours, effectively interpret the data provided by AI, and uncover the authentic issues in educational settings remain tasks that require teachers to perform (tasks that AI cannot replace). This finding aligns with the study by Kim, Curry & Fiegener (2024), which demonstrated variations in problem-solving with AI. The study posited that AI may offer school leaders support in diverse and generalised ways, while educational leaders proffered solutions that were nuanced, context-specific, and accompanied by justifications of resources and experiences that enriched discussions.

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